package com.zyf.EasyNet.util.NeuralNetwork;

/**
 * @first_author zyflzz
 * @gmt_created 2022/6/8
 * @gmt_modified 2022/6/8
 */
public class DefaultData {
    private static double[][] sample = {
            {20.55, 0.6, 0.09},
            {22.44, 0.75, 0.11},
            {25.37, 0.85, 0.11},
            {27.13, 0.9, 0.14},
            {29.45, 1.05, 0.20},
            {30.10, 1.35, 0.23},
            {30.96, 1.45, 0.23},
            {34.06, 1.6, 0.32},
            {36.42, 1.7, 0.32},
            {38.09, 1.85, 0.34},
            {39.13, 2.15, 0.36},
            {39.99, 2.2, 0.36},
            {41.93, 2.25, 0.38},
            {44.59, 2.35, 0.49},
            {47.30, 2.5, 0.56},
            {52.89, 2.6, 0.59},
            {55.73, 2.7, 0.59},
            {56.76, 2.85, 0.67},
            {59.17, 2.95, 0.69},
            {60.63, 3.1, 0.79}
    };
    private static double[][] except = {
            {5126, 1237},
            {6217, 1379},
            {7730, 1385},
            {9145, 1399},
            {10460, 1663},
            {11387, 1714},
            {12353, 1834},
            {15750, 4322},
            {18304, 8132},
            {19836, 8936},
            {21024, 11099},
            {19490, 11203},
            {20433, 10524},
            {22598, 11115},
            {25107, 13320},
            {33442, 16762},
            {36836, 18673},
            {40548, 20724},
            {42927, 20803},
            {43462, 21804}
    };

    public static double[][] getSample() {
        return sample;
    }

    public static double[][] getExcept() {
        return except;
    }
}
